Exploring resilience and competitiveness of wine estates in Languedoc-Roussillon in the recent past: a multi-level perspective

The Fruška Gora mountain is a traditional wine-growing region in Serbia situated in the Pannonian Basin. Due to such a position, the vicinity of the Danube River and the presence of concave configuration, it is suitable for grape production. This paper provides analyses of spatial variations in meteorological parameters and grape juice quality within Fruška Gora wine region over three consecutive vintages (2018-2020). The examined period can be defined as warm with cool nights during September (AVG 18,9°C; GDD 1918°C; CI 12°CF) and with the presence of mesoclimatic variability. The East part of the study area was somewhat drier and hotter compared to other parts of the region. The analyses of grape must samples (190 in total) of five cultivars (Cabernet-Sauvignon, Merlot, Chardonnay, Sauvignon blanc and Grašac (Welschriesling)) commonly grown across the region (19 sites), were performed using Fourier Transform Infrared Technology (FTIR). Among all cultivars, Sauvignon blanc was harvested first in the East area (DOY=246±5, GDD at harvest=1552±74, 22.2±0.7 °Brix), while the latest harvest was recorded for Cabernet-Sauvignon in the West (DOY=283±5, GDD at harvest=1936±187, 23.4±1.0 °Brix ). Both the red and white cultivars had higher acidity and YAN in the grape must if the vines were grown in the North and East compared to South and West areas. According to PCA analysis, Grašac showed the lowest variation in grape must chemical composition. Thus, the results confirm that Grašac is the most stable cultivar in Fruška Gora. All monitored cultivars reached technological fruit ripeness by the end of the growing season. However, it was difficult to reach full ripeness of red cultivars, mostly beacuse of uncoupling of technolocical and phenolic ripeness. Thus, Cabernet-Sauvignon had higher variations in GDD sums at harvest compared to other cultivars, which probably increased variations in grape must quality.

A gradual decline in vineyards has been observed over the past twenty years worldwide. This might be explained by the climate change, practices change or the increase of dieback diseases. To increase the longevity of vines, we studied the impact of different pruning strategies in four adult and four young vineyards located in France and Spain. In France, vineyards were planted with Cabernet franc on 3309C while Spanish trials were planted with Tempranillo grafted on 110R. Vegetative expression, yield, quality of berries and wood vessels conductivity were measured. The distribution of vegetative expression, yield and berry composition between primary and secondary vegetation were quantified. Finally, tomography was used to evaluate the implication of the treatments on sap flows.
First results show that i) the respectful pruning leads to an increase of 30 to 50% more secondary shoots than the aggressive pruning in France and between 15 and 20% in Spain, ii) there is no major effect on the yield over the first two years following the implementation of the new pruning practices, although the proportion of clusters from suckers is higher on the respectful pruning method. On young vines, the development of the trunk according to a respectful pruning leads to a loss of harvest 2 years after planting. This is due to the removal, on the future trunk, of the green suckers which carrying bunches. This operation carried out in spring rather than during winter pruning, would promote a better leaf / fruit balance when the plant comes into production, and could lead to better hydraulic conduction in the vessels of the trunk. Maintaining these trials for several years will provide more robust data to assess the impact of these practices on the vines over the long term.

Currently, the main goal of agriculture is to promote the resilience of agricultural systems in a sustainable way through the improvement of use efficiency of farm resources, increasing crop yield and quality under climate change conditions. This last is expected to drastically modify plant growth, with possible negative effects, especially in arid and semi-arid regions of Europe on the viticultural sector. In this context, the monitoring of spatial behavior of grapevine during the growing season represents an opportunity to improve the plant management, winegrowers’ incomes, and to preserve the environmental health, but it has additional costs for the farmer. Nowadays, UAS equipped with a VIS-NIR multispectral camera (blue, green, red, red-edge, and NIR) represents a good and relatively cheap solution to assess plant status spatial information (by means of a limited set of spectral vegetation indices), representing important support in precision agriculture management during the growing season. While differences between UAS-based multispectral imagery and point-based spectroscopy are well discussed in the literature, their impact on plant status estimation by vegetation indices is not completely investigated in depth. The aim of this study was to assess the performance level of UAS-based multispectral (5 bands across 450-800nm spectral region with a spatial resolution of 5cm) imagery, reconstructed high-resolution satellite (Sentinel-2A) multispectral imagery (13 bands across 400-2500 nm with spatial resolution of <2 m) through Convolutional Neural Network (CNN) approach, and point-based field spectroscopy (collecting 600 wavelengths across 400-1000 nm spectral region with a surface footprint of 1-2 cm) in a plant status estimation application, and then, using Bayesian regularization artificial neural network for leaf chlorophyll content (LCC) and plant water status (LWP) prediction. The test site is a Greco vineyard of southern Italy, where detailed and precise records on soil and atmosphere systems, in-vivo plant monitoring of eco-physiological parameters have been conducted.

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

Excell laboratory has initiated the development of an analytical method based on electrochemistry to evaluate the ability of wines to undergo or resist to oxidative phenomena. Electrochemistry is a powerful tool to probe reactions involving electron transfers and offers possibility of real-time measurements. In that context, the laboratory has implemented electrochemical analysis to assess oxidation state of different wine matrices but also in order to evaluate oxidative or reduced character of leaf and soil. Initially, our laboratory focused on dosage of compounds involved in responses of plant stresses and we were also interested in microbiological activity of soils. These analyses were compared with the measurement of redox potential (Eh) and pH which are two fundamental variables involved in the modulation of plant metabolism. Indeed, the variation of redox states of the plant reflects its biological activity but also its capacity to absorb nutriments. The Eh-pH conditions mainly determine metabolic processes involved in soil and leaf and our goal is to determine if this combined analytical approach will be sufficiently precise to detect biological evolutions (plant health, parasitic attack…).